A comprehensive introduction to sampling-based methods in statistical computing The use of computers in mathematics and statistics has opened up a wide range of techniques for studying otherwise intractable problems. Sampling-based simulation techniques are now an invaluable tool for exploring statistical models. This book gives a comprehensive introduction to the exciting area of sampling-based methods. An Introduction to Statistical Computing introduces the classical topics of random number generation and Monte Carlo methods. It also includes some advanced me
These lecture notes give a simple introduction to some main ideas and techniques used in Monte Carlo...
The sixth edition of this highly successful textbook provides a detailed introduction to Monte Carlo...
Rigorous and comprehensive, this textbook introduces undergraduate students to simulation methods in...
Sampling-based computational methods have become a fundamental part of the numerical toolset of prac...
Dealing with all aspects of Monte Carlo simulation of complex physical systems encountered in conden...
Monte Carlo methods form an experimental branch of mathematics that employs simulations driven by ra...
With the development of ever more powerful computers a new branch of physics and engineering evolved...
This book has a very large scope in that, beyond its title, it covers the dual fields of computation...
Computational techniques based on simulation have now become an essential part of the statistician's...
A comprehensive overview of Monte Carlo simulation that explores the latest topics, techniques, and ...
Traditionally, the concept of sampling distribution has been seen as fundamental to an understanding...
This book seeks to bridge the gap between statistics and computer science. It provides an overview o...
Probability and statistics are fascinating subjects on the interface between mathematics and applied...
Monte Carlo Simulation in Statistical Physics deals with the computer simulation of many-body system...
This textbook on statistical modeling and statistical inference will assist advanced undergraduate a...
These lecture notes give a simple introduction to some main ideas and techniques used in Monte Carlo...
The sixth edition of this highly successful textbook provides a detailed introduction to Monte Carlo...
Rigorous and comprehensive, this textbook introduces undergraduate students to simulation methods in...
Sampling-based computational methods have become a fundamental part of the numerical toolset of prac...
Dealing with all aspects of Monte Carlo simulation of complex physical systems encountered in conden...
Monte Carlo methods form an experimental branch of mathematics that employs simulations driven by ra...
With the development of ever more powerful computers a new branch of physics and engineering evolved...
This book has a very large scope in that, beyond its title, it covers the dual fields of computation...
Computational techniques based on simulation have now become an essential part of the statistician's...
A comprehensive overview of Monte Carlo simulation that explores the latest topics, techniques, and ...
Traditionally, the concept of sampling distribution has been seen as fundamental to an understanding...
This book seeks to bridge the gap between statistics and computer science. It provides an overview o...
Probability and statistics are fascinating subjects on the interface between mathematics and applied...
Monte Carlo Simulation in Statistical Physics deals with the computer simulation of many-body system...
This textbook on statistical modeling and statistical inference will assist advanced undergraduate a...
These lecture notes give a simple introduction to some main ideas and techniques used in Monte Carlo...
The sixth edition of this highly successful textbook provides a detailed introduction to Monte Carlo...
Rigorous and comprehensive, this textbook introduces undergraduate students to simulation methods in...